| import argparse |
| import glob |
| import numpy as np |
| import os |
| import cv2 |
| import torch |
| from torchvision.transforms.functional import normalize |
| from basicsr.utils import imwrite, img2tensor, tensor2img |
|
|
| from basicsr.utils.registry import ARCH_REGISTRY |
|
|
| if __name__ == '__main__': |
| parser = argparse.ArgumentParser() |
| parser.add_argument('-i', '--test_path', type=str, default='datasets/ffhq/ffhq_512') |
| parser.add_argument('-o', '--save_root', type=str, default='./results/vqgan_rec') |
| parser.add_argument('--codebook_size', type=int, default=1024) |
| parser.add_argument('--ckpt_path', type=str, default='./experiments/pretrained_models/vqgan/net_g.pth') |
| args = parser.parse_args() |
|
|
| if args.save_root.endswith('/'): |
| args.save_root = args.save_root[:-1] |
| dir_name = os.path.abspath(args.save_root) |
| os.makedirs(dir_name, exist_ok=True) |
|
|
| device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') |
| test_path = args.test_path |
| save_root = args.save_root |
| ckpt_path = args.ckpt_path |
| codebook_size = args.codebook_size |
|
|
| vqgan = ARCH_REGISTRY.get('VQAutoEncoder')(512, 64, [1, 2, 2, 4, 4, 8], 'nearest', |
| codebook_size=codebook_size).to(device) |
| checkpoint = torch.load(ckpt_path)['params_ema'] |
|
|
| vqgan.load_state_dict(checkpoint) |
| vqgan.eval() |
|
|
| for img_path in sorted(glob.glob(os.path.join(test_path, '*.[jp][pn]g'))): |
| img_name = os.path.basename(img_path) |
| print(img_name) |
| img = cv2.imread(img_path) |
| img = img2tensor(img / 255., bgr2rgb=True, float32=True) |
| normalize(img, (0.5, 0.5, 0.5), (0.5, 0.5, 0.5), inplace=True) |
| img = img.unsqueeze(0).to(device) |
| with torch.no_grad(): |
| output = vqgan(img)[0] |
| output = tensor2img(output, min_max=[-1,1]) |
| img = tensor2img(img, min_max=[-1,1]) |
| restored_img = np.concatenate([img, output], axis=1) |
| restored_img = output |
| del output |
| torch.cuda.empty_cache() |
|
|
| path = os.path.splitext(os.path.join(save_root, img_name))[0] |
| save_path = f'{path}.png' |
| imwrite(restored_img, save_path) |
|
|
| print(f'\nAll results are saved in {save_root}') |
|
|
|
|
